Robustness of robust process optimization

Summary

The article treats sensitivity of robust process optimization (robust design) to model estimation errors and uncertainty of the target value. Model estimation errors due to random error in the response leads to variance and bias of the optimization criterion, and uncertainty in the location of the optimal parameter setting. Methods to assess and compensate for such effects are presented. We introduce a technique for finding confidence regions for the location of the optimal parameter setting. Finally, we describe a way to assess the sensitivity to uncertainty in the target value, and present a strategy for dealing with such cases.

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DOI : doi.org/10.1081/QEN-100106882